This Is Why Edge Computing Is So Famous!

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Intel SGX technology provides hardware-level memory isolation and remote security attestation, allowing applications to open a trusted execution area, known as an enclave in memory. Malicious software, privileged software, and even the operating system on the same platform cannot be accessed without authorization, thus preventing data leakage and malicious tampering within the enclave. Therefore, in recent years, some scholars have turned to studying the decentralized access control framework in the Internet of Things.

edge computing is an extension of which technology

The public have gradually learned about blockchain technology with the rise of non-fungible tokens and the encrypted digital currency industry in recent years. Trusted computing technology, represented by intel software guard extensions technology , can execute applications in an isolated environment using secure hardware. It provides a new way to solve the problem of malicious disclosure or tampering with user privacy data through untrusted edge nodes.

Why Is Edge Computing Important?

Centrally, cloud brings data together to create new analytics and applications, which can be distributed on the edge — residing on-site or with the customer. Edge computing will also become more prevalent as IoT devices continue to flood the market. That’s why we expect edge computing to become an important part of the internet of things over the next few years and beyond.

  • Extending IT to the mission’s edge, where edge computing, bolstered by IoT and 5G connectivity, is transforming federal government.
  • And Z.L.; supervision, H.W.; project administration, M.X.; visualization, F.M.
  • Some examples of edge use cases include self-driving cars, autonomous robots, smart equipment data and automated retail.
  • Currently, the continuous delivery and deployment of blockchain-distributed software is widely and rapidly developing, and there have been many excellent works .
  • But sensors are usually connected to the internet by a wireless network.
  • The node’s identity will also be remotely authenticated when registering in the edge server’s enclave.

We deployed it on the Quorum blockchain to achieve flexible management of access policies and fine-grained access control in IoT systems. In addition, our scheme distributes attribute information to clients in the form of signatures, stores it offline, and realizes the signature check mechanism on the blockchain, saving valuable storage space on the chain. Meanwhile, combined with SGX technology, we designed the trusted processing flow of IoT data in edge servers, eliminating the possibility of malicious servers accessing data illegally. Finally, we conducted extensive experiments on Quorum blockchain and SGX-enabled servers. Through testing and analysis of comparative experiments, the performance of our framework is more advantageous in terms of gas overhead, deployment time, and storage overhead on the chain.

Cloud providers offer more than just remote apps; they also offer a wide variety of other services such as data storage and backup, online document sharing and collaboration tools,video conferencing, CRM software modules, and many more. In addition, edge computing is limited by the internet speed at each location. So, if you have several locations in different countries that need to access cloud applications or other services from the same cloud provider, you’ll only be able to do so if the provider has a presence in all regions where you operate. Most enterprise applications of edge computing take a distributed approach, according to McCarthy. “That means individual functions or modules within the application are deployed across a spectrum of on-premises, cloud, and edge infrastructure,” he says. It could also be industry-specific field locations like factories, warehouses, hospitals, and retail stores.

Cloud remains the best solution when we need to combine edge, enterprise and third-party data for discovery and AI model creation. For one thing, edge capacity is limited because edge reintroduces resource constraints on battery, bandwidth, storage and computing power. Even with these amazing benefits, edge will not replace cloud what is edge computing with example computing. But it’s at the edge where each store micro-adjusts the initial forecast with specific on-site, real-time data from their kitchen and point-of-sale systems. Using compute at the edge is how they can make sure everyone’s fries are crispy, whether it’s a slow afternoon or a crush of families after a little league game.

Sensors in agricultural fields gather valuable information, however that information does not have to be compelled to be analyzed or hold on in period of time. Edge devices will collect, kind and perform a preliminary analysis of the info, then send it on to where it has to attend centralized applications or some type of semipermanent storage, again, either on-prem or within the Cloud. As a result of this traffic might not be time-sensitive, slower, less costly connections, probably over the net, is used. And since the info is presorted, the degree of traffic that has to be sent the least bit could also be reduced.

Performance Evaluation

We completed the experimental verification in Section 5 and compared it with similar work to show the superiority of our scheme. Section 6 discusses the advantages and limitations of the framework. Finally, in Section 7, we summarize the framework of this article and discuss the direction of future research.

It also makes it easy to customize routing and bandwidth to determine how to connect edge devices to each other to the cloud. 5G makes edge implementations seamless by guaranteeing the transmission of critical control messages that enable devices to make autonomous decisions. This last-mile technology connects the edge to the internet backhaul and ensures that edge devices have the right software-defined network configurations to do the right things. The most common use case for edge computing is to store sensor data. Sensors are an important part of the modern Internet of Things ecosystem, and they generate a lot of data that might be useful for companies and other organizations. But sensors are usually connected to the internet by a wireless network.

edge computing is an extension of which technology

In that case, a large amount of data will be uploaded to the cloud data center server, inevitably leading to network delay. Edge computing uses the edge zone close to the data source to provide network services and computing power closer to the client, which should improve data processing efficiency and reduce service response delay. As the number of attributes increases, the calculation and storage overhead of blockchain contract execution will increase, so the gas cost of these four operations will also increase correspondingly. In the experimental results, the gas overhead of AddDataPol is significantly higher than that of DelDataPol. Storing new data on the blockchain will lead to excessive resource usage while deleting data will free up storage space on the blockchain and return the appropriate gas. Unqualified tokens or invalid signature and attribute sets will end early in the access control function.

Edge Computing Definitions

For the above work related to IoT access control, we summarized the characteristics of some representative studies in Table 1. Quorum is a branch of the Go language implementation version of Ethereum, developed by JPMorgan Chase Company, which reuses and extends some features of Ethereum. Quorum is an enterprise blockchain platform and a permissioned chain supporting privacy transactions. It supports confidentiality and privacy of transactions as well as PBFT consensus algorithms. Quorum is suitable for application scenarios that require high-speed transactions and high throughput to handle private transactions.

Suppose Enclave D is determined to be on the same platform as itself. In that case, Q will pack the received content into a reference structure QUOTE, sign the QUOTE, and send it to Enclave C. Enclave C first verifies the correctness of the signature. It then uses QUOTE to conduct remote attestation after verification.

This placement at the edge helps to increase operational efficiency and is responsible for many advantages to the system. The state-of-the-art scheduling technique can increase the efficiency of utilize edge resources and scales the edge server by minimum edge resources to each offloaded tasks. As edge computing continues to evolve, more uses are on the horizon. There’s a lot more at stake here than achieving faster speeds in analytics to feed automated decision-making in fluid situations.


Therefore, increasing the number of clients will not lead to an increase in blockchain storage costs. Thus, the flexibility of the proposed framework is greatly enhanced. Satoshi Nakamoto first proposed blockchain technology in his article published in 2008. It is a decentralized, distributed data ledger linked by digital blocks in chronological order. Inspired by bitcoin, Buterin put forward the concept of Ethereum in 2013, which is widely known as blockchain 2.0.

Li et al. proposed a double-layer blockchain IoT access control framework on Ethereum and Fisco. They used the linear secret sharing scheme to achieve a fine-grained access strategy. Still, the increase in the number of attributes will lead to a large amount of gas overhead on the blockchain.

Industrial Edge Computing

It offers the benefit of data collection, processing, storage and analysis in real-time for more informed and faster decision making in complex production environments. This opens up a wide range of possibilities for manufacturers that were thought to be impossible when industrialization first began. Centrally, cloud brings data together to create new analytics and applications, which will be distributed on the edge — residing on-site or with the customer. That, in turn, generates more data that feeds back into the cloud to optimize the experience. For example, when doing facial recognition to unlock a smartphone, it’s better to keep data at the edge. The AI models are trained for each user’s face without these images ever leaving the device.

For the last decade, her work has focused on the intersection of business and technology. Why an Open RAN solution is what your network needs April 7, 2022 Open RAN network infrastructure is more open, flexible, customizable and future-proof. The data can’t be transferred off-site because of security concerns or privacy regulations. The company can create a forecast in the cloud to predict how many waffle fries should be cooked per minute over a day — easy when using transactional sales data. Figure 10.Performance comparison between non-SGX-enabled and SGX-enabled machines.

Edge computing may employ virtualization technology to make it easier to deploy and run a wide range of applications on edge servers. Automated and self-improving robotic processes, prediction and maintenance automation. On-demand production, and other new capabilities are making edge computing essential for industrial robot users. Most send data through the open systems interconnection framework to pool data from different devices that follow various standards. Gateway devices frequently route, transfer, and manage data connections.

Federal Edge Solutions

With analysis of that pressure information going down at distant process centers, the automated shutoff directions could come back too late. However with process power placed native to the tip devices, latency is a smaller amount, which trip time is considerably reduced, probably saving period injury to property and even lives. Even with the introduction of edge devices that give native computing and storage, there’ll still be a desire to attach them to information centers whether or not they area unit on-premises or within the cloud. Bringing connectivity to industrial machines provides access to valuable data and enables software updates that contribute to significant improvements in productivity and efficiency on the shop floor.

In Proceedings of the Second International Conference on Internet of Things, Data and Cloud Computing, Cambridge, UK, 22–23 March 2017; Volume 7. Another use of the architecture is cloud gaming, where some aspects of a game could run in the cloud, while the rendered video is transferred to lightweight clients running on devices such as mobile phones, VR glasses, etc. Edge nodes used for game streaming are known as gamelets, which are usually one or two hops away from the client.

In order to leverage this wealth of data, that was previously unavailable and now becomes available to users, it needs to be collected, processed and analyzed. The resulting insights can then be used to develop new processes which improve machine performance. Therefore, the industrial Internet of Things vision is dependent upon technologies that are open, standard and interoperable – such as industrial edge computing. The device that stores data and sends it to the cloud can be a computer, server or even a smart phone. We assume that the ES has captured the “Permitted” event triggered by the client and downloaded the corresponding data set from IPFS.

Challenges To Implementing Edge Computing

In addition, data collection is getting closer to your daily life, and Edge Computing Work can suck more personal information from your personal life than just what you do on your device or browser. Just as providers forever change the on-premises data center model for everyone, they will also disrupt their own cloud model. The smart move is to continue to disrupt your own company to find new revenue streams and grab a bigger market share. Basically, the term refers to devices that collect and use data at the outer edge of the network. Think of edge computing as cloud computing coming to the data source. Which greatly minimizes the distance the data has to travel for analysis.

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